Spatial heterogeneity is an inherent characteristic of natural forest landscapes,therefore estimation of structural variability,including the collection and analyzing of field measurements,is a growing challenge for monitoring wildlife habitat diversity and ecosystem sustainability.In this study,we investigated the combined influence of plot shape and size on the accuracy of assessment of conventional and rare structural features in two young-growth spruce-dominated forests in northwestern China.We used a series of inventory schemes and analytical approaches.Our data showed that options for sampling protocols,especially the selection of plot size considered in structural attributes measurement,dramatically affect the minimum number of plots required to meet a certain accuracy criteria.The degree of influence of plot shape is related to survey objectives; thus,effects of plot shape differ for evaluations of the “mean” or “representative” stand structural conditions from that for the range of habitat(in extreme values).Results of Monte Carlo simulations suggested that plot sizes <0.1 ha could be the most efficient way to sample for conventional characteristics(features with relative constancy within a site,such as stem density).Also,0.25 ha or even larger plots may have a greater likelihood of capturing rare structural attributes(features possessing high randomness and spatial heterogeneity,such as volume of coarse woody debris) in our forest type.These findings have important implications for advisable sampling protocol(plot size and shape) to adequately capture information on forest habitat structure and diversity; such efforts must be based on a clear definition of which types are structural attributes to measure. Spatial heterogeneity is an inherent characteristic of natural forest landscapes, therefore estimation of structural variability, including the collection and analyzing of field measurements, is a growing challenge for monitoring wildlife habitat diversity and ecosystem sustainability. This study, we investigated the combination influence of plot shape and size on the accuracy of assessment of conventional and rare structural features in two young-growth spruce-dominated forests in northwestern China. We used a series of inventory schemes and analytical approaches. Our data showed that options for sampling protocols, especially the selection of plot size considered in structural attributes measurement, dramatically affect the minimum number of plots required to meet a certain accuracy criteria.The degree of influence of plot shape is related to survey objectives; thus, effects of plot shape differ for evaluations of the “ mean ”or “ representative ”stand structural conditions from that for the Results of Monte Carlo simulations suggested that plot sizes <0.1 ha could be the most efficient way to sample for conventional characteristics (features with relative constancy within a site, such as stem density). Also, 0.25 ha or even larger plots may have a greater likelihood of capturing rare structural attributes (features possessing high randomness and spatial heterogeneity, such as volume of coarse woody debris) in our forest type. These findings have important implications for advisable sampling protocol (plot size and shape) to adequately capture information on forest habitat structure and diversity; such efforts must be based on a clear definition of which types are structural attributes to measure.